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PyTorch Deep Learning Projects: Build and Deploy Intelligent AI Solutions with Code-Driven Workflows
Master PyTorch Deep Learning
—From Fundamentals to Production-Ready AI Applications
PyTorch Deep Learning Build and Deploy Intelligent AI Solutions with Code-Driven Workflows is the ultimate hands-on guide for developers, data scientists, and engineers ready to turn cutting-edge deep learning theory into powerful real-world solutions.
Through a unique project-based learning approach, this comprehensive guide walks you through every step—from model design to deployment—using modern PyTorch 2.x best practices.
What Makes This Book Stand Out
• Real-World AI Projects: Build image classifiers, NLP APIs, time series forecasters, GANs, and more.
• Modern Workflows: Leverage PyTorch Lightning, Hugging Face, Docker, and MLOps tools.
• Production-Ready Techniques: Optimize models with quantization, TorchScript, and ONNX.
• Full-Stack AI Engineering: Train, explain, deploy, and monitor models with real tools in real environments.
You’ll Learn How To
• Build and train neural networks with nn.Module, autograd, and custom architectures
• Work with CNNs, RNNs, LSTMs, Transformers, BERT, and GANs
• Fine-tune foundation models using PEFT, LoRA, and Hugging Face Transformers
• Deploy APIs using FastAPI, containerize models with Docker, and scale using cloud services
• Use Grad-CAM, SHAP, and LIME for model explainability
• Automate workflows with GitHub Actions, MLflow, and CI/CD pipelines
Who This Book Is For
• Machine Learning Beginners seeking a structured, project-driven pathway
• AI Engineers & Data Scientists who want to sharpen their PyTorch production skills
• Software Developers & Tech Enthusiasts aiming to break into the AI field with confidence
• Educators & Students needing a practical, up-to-date PyTorch learning resource
Inside This Book
• 14 expertly crafted chapters + 5 bonus appendices
• Step-by-step walkthroughs of practical deep learning challenges
• Fully flowcharts, code blocks, comparison tables, and project blueprints
• Structured for SEO, clarity, and KDP A+ content standards
From training deep neural networks to deploying intelligent AI systems—this book equips you with the skills to build real impact.
Grab your copy today and start building with PyTorch like a pro.
PyTorch Deep Learning Build and Deploy Intelligent AI Solutions with Code-Driven Workflows is the ultimate hands-on guide for developers, data scientists, and engineers ready to turn cutting-edge deep learning theory into powerful real-world solutions.
Through a unique project-based learning approach, this comprehensive guide walks you through every step—from model design to deployment—using modern PyTorch 2.x best practices.
What Makes This Book Stand Out
• Real-World AI Projects: Build image classifiers, NLP APIs, time series forecasters, GANs, and more.
• Modern Workflows: Leverage PyTorch Lightning, Hugging Face, Docker, and MLOps tools.
• Production-Ready Techniques: Optimize models with quantization, TorchScript, and ONNX.
• Full-Stack AI Engineering: Train, explain, deploy, and monitor models with real tools in real environments.
You’ll Learn How To
• Build and train neural networks with nn.Module, autograd, and custom architectures
• Work with CNNs, RNNs, LSTMs, Transformers, BERT, and GANs
• Fine-tune foundation models using PEFT, LoRA, and Hugging Face Transformers
• Deploy APIs using FastAPI, containerize models with Docker, and scale using cloud services
• Use Grad-CAM, SHAP, and LIME for model explainability
• Automate workflows with GitHub Actions, MLflow, and CI/CD pipelines
Who This Book Is For
• Machine Learning Beginners seeking a structured, project-driven pathway
• AI Engineers & Data Scientists who want to sharpen their PyTorch production skills
• Software Developers & Tech Enthusiasts aiming to break into the AI field with confidence
• Educators & Students needing a practical, up-to-date PyTorch learning resource
Inside This Book
• 14 expertly crafted chapters + 5 bonus appendices
• Step-by-step walkthroughs of practical deep learning challenges
• Fully flowcharts, code blocks, comparison tables, and project blueprints
• Structured for SEO, clarity, and KDP A+ content standards
From training deep neural networks to deploying intelligent AI systems—this book equips you with the skills to build real impact.
Grab your copy today and start building with PyTorch like a pro.
221 pages, Kindle Edition
Published May 16, 2025
1 person is currently reading
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